Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px


init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
# YOUR CODE HERE
# Filter data for the year 2007
df_2007 = df[df['year'] == 2007]

# Sort the data by continent and population
df_2007_sorted = df_2007.sort_values(by=['continent', 'pop']).groupby('continent').sum().reset_index()


# Create the barplot
fig = px.bar(
    df_2007_sorted,
    x = 'pop',
    y = 'continent',
    color= 'continent',  # Different colors for each continent
    title= 'Population of Continents in 2007'
)

# Customize layout of the figure
fig.update_layout(
    showlegend=False,  # Hide legend
)

# Show the plot
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
# YOUR CODE HERE
# Filter data for the year 2007
df_2007 = df[df['year'] == 2007]

# Sort the data by continent and population
df_2007_sorted = df_2007.sort_values(by=['continent', 'pop']).groupby('continent').sum().reset_index()


# Create the barplot
fig = px.bar(
    df_2007_sorted,
    x = 'pop',
    y = 'continent',
    color= 'continent',  # Different colors for each continent
    title= 'Population of Continents in 2007'
)

# Customize layout of the figure
fig.update_layout(
    showlegend=False,  # Hide legend,
    yaxis={'categoryorder': 'total ascending'}   # Sort the order of the continent for the visualisation
)


# Show the plot
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [26]:
# YOUR CODE HERE
# Filter data for the year 2007
df_2007 = df[df['year'] == 2007]

# Sort the data by continent and population
df_2007_sorted = df_2007.sort_values(by=['continent', 'pop']).groupby('continent').sum().reset_index()


# Create the barplot
fig = px.bar(
    df_2007_sorted,
    x = 'pop',
    y = 'continent',
    color= 'continent',  # Different colors for each continent
    text_auto='.2s',
    title= 'Population of Continents in 2007'
)

# Customize layout of the figure
fig.update_layout(
    showlegend=False,  # Hide legend,
    yaxis={'categoryorder': 'total ascending'},   # Sort the order of the continent for the visualisation
)


# Show the plot
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [6]:
# YOUR CODE HERE

# Sort the data by continent and population
df_sorted = df.sort_values(by=['continent', 'pop'])


# Create the barplot
animated_fig = px.histogram(
    df_sorted,
    x = 'pop',
    y = 'continent',
    color= 'continent',  # Different colors for each continent
    title= 'Population of Continents over time'
)

# Create animation
animated_fig = px.histogram(df, x="pop", y="continent", color="continent",
        animation_frame="year", range_x=[0,4000000000])

# Customize layout of the figure
animated_fig.update_layout(
    showlegend=False,  # Hide legend,
    yaxis={'categoryorder': 'total ascending'},   # Sort the order of the continent for the visualisation
)

# Show figure
animated_fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [16]:
# YOUR CODE HERE
# Create animation
animated_fig = px.histogram(df, x="pop", y="country", color="country",
        animation_frame="year", range_x=[0,1400000000])

# Customize layout of the figure
animated_fig.update_layout(
        showlegend=False,  # Hide legend,
        yaxis={'categoryorder': 'total ascending'},   # Sort the order of the continent for the visualisation
        title= 'Population of Countries over time'
)

# Show figure
animated_fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [20]:
# YOUR CODE HERE
# Create animation
animated_fig = px.histogram(df, x="pop", y="country", color="country",
        animation_frame="year", range_x=[0,1400000000])

# Customize layout of the figure
animated_fig.update_layout(
    showlegend=False,  # Hide legend,
    yaxis={'categoryorder': 'total ascending'},   # Sort the order of the continent for the visualisation
    height=1000,
    title= 'Population of Countries over time'
)

# Show figure
animated_fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [25]:
# YOUR CODE HERE

# # Sort the data by continent and population
# df_sorted = df.sort_values(by=['country', 'pop'])


# # Create the barplot
# animated_fig = px.histogram(
#     df_sorted,
#     x = 'pop',
#     y = 'country',
#     color= 'country',  # Different colors for each continent
#     title= 'Population of Top 10 Countries over time'
# )

# Create animation
animated_fig = px.histogram(df,
                            x="pop", 
                            y="country", 
                            color="country",
                            animation_frame="year", 
                            range_x=[0,1400000000],
                            range_y=[131.5,142]
                            
)

# Customize layout of the figure
animated_fig.update_layout(
    showlegend=False,        
    yaxis={'categoryorder': 'total ascending'},
    height=1000,
    title='Population of Top 10 Countries over time'
)

# Show figure
animated_fig.show()
In [ ]: